Exploring potential of different X-ray imaging methods for early-stage lung cancer detection

Kun Li; Yu Chen; Rui Sun; Bei Yu; Gang Li; Xiaoming Jiang

doi:10.1007/s41605-020-00173-1

Exploring potential of different X-ray imaging methods for early-stage lung cancer detection

Kun Li, Yu Chen^*, Rui Sun, Bei Yu, Gang Li, Xiaoming Jiang

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

Purpose: To explore the potential of X-ray imaging for early-stage lung cancer screening and to help finding an optimal lung cancer screening method. Methods: Experimentally and simulatively comparing performances of different X-ray techniques (absorption-contrast imaging and phase-contrast imaging) for model lung cancer samples. Results: Absorption imaging shows performance equal to or better than that of low-radiation dose. Conclusion: Absorption imaging is still the most promising imaging method for early lung cancer detection.

Original language	English
Pages (from-to)	213-221
Number of pages	9
Journal	Radiation Detection Technology and Methods
Volume	4
Issue number	2
DOIs	https://doi.org/10.1007/s41605-020-00173-1
Publication status	Published - 1 Jun 2020
Externally published	Yes

Keywords

Lung cancer screening
Monte Carlo simulation
X-ray absorption-contrast imaging
X-ray phase-contrast imaging

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s41605-020-00173-1

Cite this

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title = "Exploring potential of different X-ray imaging methods for early-stage lung cancer detection",

abstract = "Purpose: To explore the potential of X-ray imaging for early-stage lung cancer screening and to help finding an optimal lung cancer screening method. Methods: Experimentally and simulatively comparing performances of different X-ray techniques (absorption-contrast imaging and phase-contrast imaging) for model lung cancer samples. Results: Absorption imaging shows performance equal to or better than that of low-radiation dose. Conclusion: Absorption imaging is still the most promising imaging method for early lung cancer detection.",

keywords = "Lung cancer screening, Monte Carlo simulation, X-ray absorption-contrast imaging, X-ray phase-contrast imaging",

author = "Kun Li and Yu Chen and Rui Sun and Bei Yu and Gang Li and Xiaoming Jiang",

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year = "2020",

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doi = "10.1007/s41605-020-00173-1",

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T1 - Exploring potential of different X-ray imaging methods for early-stage lung cancer detection

AU - Li, Kun

AU - Chen, Yu

AU - Sun, Rui

AU - Yu, Bei

AU - Li, Gang

AU - Jiang, Xiaoming

PY - 2020/6/1

Y1 - 2020/6/1

N2 - Purpose: To explore the potential of X-ray imaging for early-stage lung cancer screening and to help finding an optimal lung cancer screening method. Methods: Experimentally and simulatively comparing performances of different X-ray techniques (absorption-contrast imaging and phase-contrast imaging) for model lung cancer samples. Results: Absorption imaging shows performance equal to or better than that of low-radiation dose. Conclusion: Absorption imaging is still the most promising imaging method for early lung cancer detection.

AB - Purpose: To explore the potential of X-ray imaging for early-stage lung cancer screening and to help finding an optimal lung cancer screening method. Methods: Experimentally and simulatively comparing performances of different X-ray techniques (absorption-contrast imaging and phase-contrast imaging) for model lung cancer samples. Results: Absorption imaging shows performance equal to or better than that of low-radiation dose. Conclusion: Absorption imaging is still the most promising imaging method for early lung cancer detection.

KW - Lung cancer screening

KW - Monte Carlo simulation

KW - X-ray absorption-contrast imaging

KW - X-ray phase-contrast imaging

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JO - Radiation Detection Technology and Methods

JF - Radiation Detection Technology and Methods

IS - 2

ER -

Exploring potential of different X-ray imaging methods for early-stage lung cancer detection

Abstract

Keywords

UN SDGs

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